What are the parameters for the FFT function in NumPy?
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What are the parameters for the FFT function in NumPy?
The FFT function in NumPy, numpy.fft.fft, has several parameters including:
a: The input array.n: Length of the FFT. If not specified, it defaults to the length of the input array.axis: The axis over which to compute the FFT. Default is -1.norm: Normalization mode. Options are None, 'backward', 'ortho', or 'forward'.
Can you explain what the norm parameter does?
Sure! The norm parameter controls the normalization of the output.
- If set to None, no normalization is applied.
- 'backward' means the output is scaled by 1/N, where N is the length of the input.
- 'ortho' normalizes the output to ensure that the inverse FFT is also an FFT, and 'forward' scales the output by N.
What happens if I don't specify the n parameter?
If you don't specify the n parameter, the FFT will compute the transform of the input array using its length. This means the output will have the same length as the input.
Can I perform an inverse FFT using NumPy?
Yes, you can perform an inverse FFT using numpy.fft.ifft. It takes the same parameters as fft, allowing you to specify the input array and other options.
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